• 센서학회지
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• 제28권3호
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• pp.164-170
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• 2019

In this paper, a lane detection and tracking algorithm based on vision sensors and employing a robust filter for inner edge detection is proposed for developing a lane departure warning system (LDWS). The lateral offset value was precisely calculated by applying the proposed filter for inner edge detection in the region of interest. The proposed algorithm was subsequently compared with an existing algorithm having lateral offset-based warning alarm occurrence time, and an average error of approximately 15ms was observed. Tests were also conducted to verify whether a warning alarm is generated when a driver departs from a lane, and an average accuracy of approximately 94% was observed. Additionally, the proposed LDWS was implemented as an embedded system, mounted on a test vehicle, and was made to travel for approximately 100km for obtaining experimental results. Obtained results indicate that the average lane detection rates at day time and night time are approximately 97% and 96%, respectively. Furthermore, the processing time of the embedded system is found to be approximately 12fps.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.163-166
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• 2000

Real-time traffic detection scheme based on Computer Vision is capable of efficient traffic control using automatically computed traffic information and obstacle detection in moving automobiles. Traffic information is extracted by segmenting vehicle region from road images, in traffic detection system. In this paper, we propose the advanced segmentation of vehicle from road images using multiple local region information. Because multiple local region overlapped in the same lane is processed sequentially from small, the traffic detection error can be corrected.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.570-574
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• 1990

Detection of left ventricular boundary for the functional analysis of LV(left ventricle)is obtained using automatic boundary detection algorithm based on dynamic programming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge. detection methods. The left ventricular diastolic volume and systolic volume and systolic volume were computed after this automatic boundary detection, and these Volume data wm applied to analyze LV ejection fraction.

• 대한교통학회:학술대회논문집
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• 대한교통학회 1995년도 제28회 학술발표회
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• pp.77-107
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• 1995

This paper documents the development of a fuzzy logic based incident detection model for urban diamond interchanges. Research in incident detection for intersections and arterials is at a very initial stage. Existing algorithms are still far from being robust in dealing with the difficulties related with data availability and the multi-dimensional nature of the incident detection problem. The purpose of this study is to develop a new real-time incident detection model for urban diamond interchanges. The development of the algorithm is based on fuzzy logic. The incident detection model developed through this research is capable of detecting lane¬blocking incidents when their effects are manifested by certain patterns of deterioration in traffic conditions and, thereby, adjustments in signal control strategies are required. The model overcomes the boundary condition problem inherent in conventional threshold-based concepts. The model captures system-wide incident effects utilizing multiple measures for more accurate and reliable detection, and serves as a component module of a real-time traffic adaptive diamond interchange control system. The model is designed to be readily scalable and expandable for larger systems of arterial streets. The prototype incident detection model was applied to an actual diamond interchange to investigate its performance. A simulation study was performed to evaluate the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy logic based approach to incident detection is promising.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1345-1360
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• 2016

In this paper, we propose a new real-time human detection under omni-directional cameras for visual surveillance purpose, based on CNN with unified detection and AGMM. Compared to CNN-based state-of-the-art object detection methods. YOLO model-based object detection method boasts of very fast object detection, but with less accuracy. The proposed method adapts the unified detecting CNN of YOLO model so as to be intensified by the additional foreground contextual information obtained from pre-stage AGMM. Increased computational time incurred by additional AGMM processing is compensated by speed-up gain obtained from utilizing 2-D input data consisting of grey-level image data and foreground context information instead of 3-D color input data. Through various experiments, it is shown that the proposed method performs better with respect to accuracy and more robust to environment changes than YOLO model-based human detection method, but with the similar processing speeds to that of YOLO model-based one. Thus, it can be successfully employed for embedded surveillance application.

• 한국위성정보통신학회논문지
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• 제11권3호
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• pp.119-122
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• 2016

특징 검출 기법은 원하는 신호에 대한 부분적인 정보가 수신단에 알려진 상황에서 정확도 높은 검출이 가능한 기법으로 알려져 있다. 이러한 방식의 검출 기법은 잡음이 강한 환경을 위해 제안되었다. 사이클로스테이셔너리 검출은 인지 무선 시스템에서 스펙트럼 검출 기법의 하나의 예이다. 그러나 이 기법은 원하는 신호에 대한 많은 양의 정보와 처리 시간을 요구한다. 반면, 에너지 검출 기반의 스펙트럼 검출은 단순한 기법으로 널리 알려져 있다. 그러나 에너지 검출은 잡음의 영향을 많이 받으며 이로 인한 검출 오류가 많이 발생하게 된다. 본 논문에서는 에너지와 사이클로스테이셔너리 기반의 기법을 결합하여 검출의 정확도를 높이는 한편 계산량과 처리 시간을 감소시키는 기법을 제안한다. 2단계의 문턱값을 이용하여 사이클로스테이셔너리 기법의 복잡도와 처리시간을 단축하여 시스템의 전송 효율을 증가시킨다. 시뮬레이션 결과 에너지 기반 사이클로스테이셔너리 검출 기법은 신호 검출에 소요되는 시간을 상당히 감소시키는 반면 시스템의 성능을 향상시킴을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1880-1884
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• 2004

The wavelet packet transform has been applied for QRS detection with squaring, window integration, and impulse filter techniques to cut down the false detection of QRS complex. This real time QRS detection has been performed on Simulink and Matlab. The correct QRS detection rates have reached to 99.75% in the experiment with 15 sets of ECG data from European ST-T database which are kept in Physionet.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.221-237
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• 2015

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제50권9호
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• pp.445-452
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• 2001

Two switching signal patterns are proposed to prevent short circuit of PWM ac choppers. The voltage detection method and the current detection method are proposed to execute two switching signal patterns. In the voltage detection method, the dead-time has to be inserted to the switching signals after polarity of input voltage is checked by voltage transducer at input side. In the current detection method, the direction of load current is checked by current transducer at output side, and the dead-time delay is not considered. Controlling circuit built by current detection method is simple because the dead-time delay is considered. The experimental results are presented to prevent short circuit of ac chopper safely.

• Bulletin of the Korean Chemical Society
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• 제26권2호
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• pp.268-272
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• 2005

Different detection characteristics of fluorescence immunochromatography method and high performance liquid chromatography (HPLC) method for the analysis of cyanobacterial toxins were studied. In particular, low and high limits of detection, detection time and reproducibility and detectable microcystin species were compared when fluorescence immunochromatography method and high performance liquid chromatography method were applied for the detection of microcystin (MC), a cyclic peptide toxin of the freshwater cyanobacterium Microcystis aeruginosa. A Fluorescence immunochromatography assay system has the unique advantages of short detection time and low detection limit, and high performance liquid chromatography detection method has the strong advantage of individual quantifications of several species of microcystins.